‘A Ct for your EV’

Introducing our proprietary, non-invasive CT (Computed Tomography) scanner for complete EV (Electric Vehicle) battery packs integrated with our ML software to detect and analyse microscopic physical faults —all within minutes.

Uncovering The Blindspot IN Ev Battery Diagnostics

Critical physical issues such as undetected cracks and leaks, creating room for risks to performance, safety, and reliability. This deficiency leads to early deterioration, increased risk of battery fires, and premature recycling—wasting valuable resources.

INNER bridges this gap, providing a complete picture. To be used alongside the ‘State of Health’ and ‘State of Charge’ testing; What we like to call: ‘State of integrity’. Our solution provides a rapid, precise, diagnosis of a wide range of physical faults, pinpointing their exact location. This empowers the user to make informed decisions concerning safety, quality, reuse and/or recycling with confidence.

With a long-term solution-based vision, we are the first to create a global database for EV pack integrity. Our advanced CT/X-ray imaging technology, coupled with AI tools and our proprietary hardware/software solution, performs a thorough analysis, examining entire battery packs down to the cell level.

INNER’s methodology delivers unparalleled insights, in minutes, maintaining the required high throughput while adapting to your workflow, thereby setting a new and improved standard for diagnostics and battery management.

In the image of a complete Renault Zoe battery pack, it is possible to analyse the integrity of the cells and connections between them, allowing to identify any leakage, swelling, and a wide variety of other physical deformations.*

INNER’s Data-Driven Solution

At INNER, we believe this will become the next industry protocol—offering reduced testing duration and manual labor. INNER paves the way to a new era of standardised automated testing. In an industry heavily dependent on manual labor and lengthy testing process. With a fast, automated, and, most of all, precise solution, it becomes the essential Industry 4.0 approach needed to scale Fix/Reuse/Recycle scenarios effectively.

Here you can see the demonstration of a 3-dimensional scan of a complete BMW i3 battery pack. With a CT-scan it is possible to distinguish between different layers within the module, detecting the smallest tears and cracks.*

*taken in collaboration with Fraunhofer EZRT— of BMW.